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   土壤om 在 农艺学 分类中 的翻译结果: 查询用时:0.019秒
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土壤om
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  soil om
    There existed significant relationship between OM and available nutrient contents in soil and various soil granule contents. Soil OM and K contents were positively correlated with soil clay (<0.002mm) and silt (0.002~0.02mm) contents, but negatively correlated with soil sand ( 0.02 ~2mm) content.
    土壤中OM和大部分速效养分含量与土壤各级颗粒含量之间均有一定的相关性 ,其中土壤OM和K含量与粘粒 (<0 .0 0 2mm)和粉粒 (0 .0 0 2~ 0 .0 2mm)含量之间均呈极显著的正相关 ,与砂粒 (0 .0 2~ 2mm)含量之间呈极显著的负相关 ;
短句来源
    Among the factors,elevation,type of rock,type of soil,landuse,PC 4 and PC 2 (two indexes of vegetation coverage) are considered as the most important variables for predicting soil OM.
    其中 ,高程、岩石类型、土属类型和反映植被覆盖度的PC4 、PC2 以及土地利用类型对于研究区土壤OM等级预测更为重要。
短句来源
    The result showed that great difference among farmer's fertilization rates was found, and relative too much P was used, whereas K was too less. Variation coefficients of soil OM, (NH_4~+-N), P, K, Ca, Mg and S fluctuated between 28.4% and 69.2%.
    结果表明,农户施肥水平差别较大,整体上施磷相对过多,施钾相对较少,土壤OM、NH4+-N、P、K、Ca、Mg和S的变异系数在28.4%~69.2%之间。
短句来源
    Soil OM and NH_4~+-N presented strong spatial dependence, and soil P,K, Ca, Mg and S moderate spatial dependence. Isoline maps of soil nutrients indicated that spatial distribution of OM was similar to gradual change of soil texture;
    土壤各养分的空间变异结构有较大区别,土壤OM及NH4+-N的变异具有强烈空间相关性,土壤P、K、Ca、Mg和S养分含量的变异为中等空间相关性。
短句来源
    The structure of soil spatial variation change with sampling intensities and soil properties. Variation of soil pH, NH4+-N, P and S was best fitted with their corresponding semi-variation model, respectively, whereas that of soil OM, Ca and Mg could be simulated by the same one model.
    土壤空间变异结构在不同采样密度下的变化随土壤的特性而定,土壤pH、NH4+-N、P及S的变异分别符合不同的半方差模型,土壤OM、Ca及Mg则均符合同一模型;
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  “土壤om”译为未确定词的双语例句
    By analyzing the factors such as elevation,type of the rock,type of the soil,PC 4,PC 2,land uses,PC 3,PC 1,upslope contributing area,slope,exposure,plane curvature and profile curvature,the classification tree can predict distribution of soil organic matter levels.
    树分析选取了高程、岩石类型、土属类型、PC4 、PC2 、土地利用类型、PC3、PC1、上坡贡献面积、坡度、坡向、平面曲率和剖面曲率来预测研究区土壤OM等级的分布。
短句来源
    There was a medium spatial correlation among the Fe,P,K,B and Mn of soil,and a strong spatial correlation among the OM,N,Ca,Mg,S,Cu and Zn of soil.
    许多土壤养分含量的空间变异结构明显 ,土壤Fe、P、K、B、Mn具有中等强度的空间相关特征 ,土壤OM、N、Ca、Mg、S、Cu、Zn具有较强的空间相关特征。
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  soil om
No significant relationship of soil pH and soil OM with AM colonization and with spore population was observed.
      
The C/N ratio was lowest in the F layer, and the highest in the H layer, indicating that soil OM is depleted in N in relation to C along the vertical soil gradient.
      
Contrary to our expectations, however, the differences in the chemical quality in soil OM between the site types were amplified from the L to the H layer.
      
Unfertilized sesbania and natural fallows cycled soil P through plant residues, resulting in increased P in soil microbial biomass immediately after the fallows and increased P in light fraction soil OM for three post-fallow cropping seasons.
      
Light-fraction OM accounted for up to38% of total soil OM and was responsible for almost all the OM accretion duringfallow.
      
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Particles in dam system soil are component mainly of silt, and its amount account for 66~70 percent in the soil. The marked difference in various soil are that there are many fine silt and clay but rather less for coarse silt and sany in strong accumulation clay layer, the loamy layer are just the contrary. The amount of OM,TN are primany concentrated on fine particles (<0005mm), the concentration difference of OM, TN between coarse and fine particles are larger in dam system soil, but TP,TK are smaller....

Particles in dam system soil are component mainly of silt, and its amount account for 66~70 percent in the soil. The marked difference in various soil are that there are many fine silt and clay but rather less for coarse silt and sany in strong accumulation clay layer, the loamy layer are just the contrary. The amount of OM,TN are primany concentrated on fine particles (<0005mm), the concentration difference of OM, TN between coarse and fine particles are larger in dam system soil, but TP,TK are smaller. The concentration of various zinc forms in the soil was found to increase progressively with fine of soil particles and the concentration increase suddenly in the fine particles (<0005mm). Therefore the highest content of OM,TN,AZn exist in strong accumulation clay layer. The above mentioned have showed the cause for nutrient condition difference in various location of dam system soil under the migration-illuviation process.

坝系土壤粒径均以粉粒为主,含量占土壤的66%~70%。各土壤间粉粒含量差异很小,所不同的是,坝地富粘层粗粉粒少细粉粒多,砂粒少粘粒多,坝、坡轻壤层反之。土壤OM、TN主要集中在粘粒中,其浓度在粗细颗粒中差别悬殊。TP及TK在粗细颗粒中这种差别就较小。土壤中各形态锌均随着土壤颗粒变细而浓度增加,在<0.005mm粒径中浓度陡然提高。故坝地富粘层中OM、TN、AZn的含量最丰。上述粒径及养分分布特点,揭示了在泥沙迁移淤积过程中,坝地不同部位土壤养分差异的内在原因。

Spatial distribution of soil available nutrient content and relationship between soil nutrient and soil granule composition for grain crop region (470km 2) in Yutian County were studied. The results indicated that soil N, P, K, Mn, and Zn were widely deficient. A remarkable spatial distribution was found in soil OM, and mainly available nutrient contents. The grain crop region could be divided into 2 to 3 management units, and each unit was consisted of connected fields. The number of management units for grain...

Spatial distribution of soil available nutrient content and relationship between soil nutrient and soil granule composition for grain crop region (470km 2) in Yutian County were studied. The results indicated that soil N, P, K, Mn, and Zn were widely deficient. A remarkable spatial distribution was found in soil OM, and mainly available nutrient contents. The grain crop region could be divided into 2 to 3 management units, and each unit was consisted of connected fields. The number of management units for grain crop region were 2 for N, 3 for P, 3 for K, 3 for Mn, 2 for Zn.There existed significant relationship between OM and available nutrient contents in soil and various soil granule contents. Soil OM and K contents were positively correlated with soil clay (<0.002mm) and silt (0.002~0.02mm) contents, but negatively correlated with soil sand ( 0.02 ~2mm) content. On the contrary, P and Mn contents were negatively correlated with soil clay and silt contents, but positively correlated with soil sand contents. Soil Zn content was negatively correlated to soil silt content, positively related to soil sand content.

对面积约 4 70km2 的玉田县粮田耕层土壤养分的空间格局及其与土壤颗粒组成之间的关系进行了研究。结果表明 ,土壤N、P、K、Mn和Zn普遍缺乏 ;土壤OM和主要速效养分含量均呈现较明显的空间分布格局 ,对土壤主要养分N、P、K、Mn和Zn可分别分成 2、3、3、3和 2个养分分区 ,因而对这 5个土壤养分进行分区管理可行。土壤中OM和大部分速效养分含量与土壤各级颗粒含量之间均有一定的相关性 ,其中土壤OM和K含量与粘粒 (<0 .0 0 2mm)和粉粒 (0 .0 0 2~ 0 .0 2mm)含量之间均呈极显著的正相关 ,与砂粒 (0 .0 2~ 2mm)含量之间呈极显著的负相关 ;而土壤P和Mn含量与粘粒和粉粒含量之间均是极显著的负相关 ,与砂粒含量之间是极显著的正相关 ;土壤Zn含量与粉粒含量之间为极显著的负相关 ,与砂粒含量之间为显著的正相关

Based on the case study of Longyou County,Zhejiang Province,an approach was introduced to deducing and expressing spatial distribution of soil organic matter. This is a kind of data mining method or classification tree modeling method,which associates soil OM content with some extensive easily observable landscape attributes,such as landform,geology,landuse and remote sensing images,thus transferring the soil OM-related information into a clear,quantitative,landscape factor-associated regular system. This system...

Based on the case study of Longyou County,Zhejiang Province,an approach was introduced to deducing and expressing spatial distribution of soil organic matter. This is a kind of data mining method or classification tree modeling method,which associates soil OM content with some extensive easily observable landscape attributes,such as landform,geology,landuse and remote sensing images,thus transferring the soil OM-related information into a clear,quantitative,landscape factor-associated regular system. This system can be used to predict continuous soil OM spatial distribution. By analyzing the factors such as elevation,type of the rock,type of the soil,PC 4,PC 2,land uses,PC 3,PC 1,upslope contributing area,slope,exposure,plane curvature and profile curvature,the classification tree can predict distribution of soil organic matter levels. Among the factors,elevation,type of rock,type of soil,landuse,PC 4 and PC 2 (two indexes of vegetation coverage) are considered as the most important variables for predicting soil OM. Results of the prediction show a quite close relationship between soil OM contents and types of the landscape sorted by the classification tree with an accuracy of 81.1%.

以浙江省龙游县研究区为例 ,提供了一种推断和表达土壤有机质 (OM)含量空间分布信息的方法 ,通过一种数据挖掘方法———分类树建模方法将土壤OM含量与一些易于广泛观测的景观属性 ,包括地形、地质、土地利用和遥感影像建立联系 ,从而将有关土壤OM含量分布的知识转入一种清楚的、定量的、与景观因子相关联的规则系统中 ,并以此来预测研究区土壤OM水平的连续空间分布。树分析选取了高程、岩石类型、土属类型、PC4 、PC2 、土地利用类型、PC3、PC1、上坡贡献面积、坡度、坡向、平面曲率和剖面曲率来预测研究区土壤OM等级的分布。其中 ,高程、岩石类型、土属类型和反映植被覆盖度的PC4 、PC2 以及土地利用类型对于研究区土壤OM等级预测更为重要。从分析结果来看 ,依据分类树所划分出的景观类型与土壤OM含量有着较好的关联性

 
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